A method was established for the simultaneous determination of sugar alcohols, erythritol, xylitol, sorbitol, inositol, mannitol, maltitiol, lactitol and isomalt by High Performance Liquid Chromatography (HPLC). The sugar alcohols were converted into strong ultraviolet (UV)-absorbing derivatives with p-nitrobenzoyl chloride (PNBC). HPLC was performed on Imtakt Unison US-
The multiclass pesticide multiresidue method for the simultaneous determination of diflubenzuron in agricultural products was conducted by using HPLC-UVD. The method was validated through the guidelines of linearity, specificity, limit of detection (LOD), limit of quantification (LOQ), accuracy and precision with pesticide-free spinach, Korean cabbage, eggplant, squash, sweet pepper, cucumber, Korean melon. The calibration curve of diflubenzuron was linear over the concentration range of 0.05-5 mg/kg with correlation coefficient of above 0.99999. The limit of detection and quantification was 0.008 and 0.02 mg/kg. Mean recoveries of diflubenzuron for each sample were 77.5-105.6%. Relative standard deviation (RSD) in recoveries were all less than 20%. The intra-day and inter-day precision (RSD) were 0.4-1.9% and 0.7-1.9%, respectively. The result of validation indicated that this method was accurate and rapid assay.
A determination method of aromatic amino acids such as trytophan (Trp), tyrosine (Tyr), and phenylalanine (Phe) using luminol-
The rapid on-site measurement of hydroponic nutrients allows for the more efficient use of crop fertilizers. This paper reports on the development of an embedded on-site system consisting of multiple ion-selective electrodes (ISEs) for the real-time measurement of the concentrations of macronutrients in hydroponic solutions. The system included a combination of PVC ISEs for the detection of NO3, K, and Ca ions, a cobalt-electrode for the detection of H2PO4, a double-junction reference electrode, a solution container, and a sampling system consisting of pumps and valves. An Arduino Due board was used to collect data and to control the volume of the sample. Prior to the measurement of each sample, a two-point normalization method was employed to adjust the sensitivity followed by an offset to minimize potential drift that might occur during continuous measurement. The predictive capabilities of the NO3 and K ISEs based on PVC membranes were satisfactory, producing results that were in close agreement with the results of standard analyzers (R2 = 0.99). Though the Ca ISE fabricated with Ca ionophore II underestimated the Ca concentration by an average of 55%, the strong linear relationship (R2 > 0.84) makes it possible for the embedded system to be used in hydroponic NO3, K, and Ca sensing. The cobalt-rod-based phosphate electrodes exhibited a relatively high error of 24.7±9.26% in the phosphate concentration range of 45 to 155 mg/L compared to standard methods due to inconsistent signal readings between replicates, illustrating the need for further research on the signal conditioning of cobalt electrodes to improve their predictive ability in hydroponic P sensing.
Pfiesteria piscicida is one of heterotrophic dinoflagellate having toxic metaboliges, and it is difficult to detect and quantify this dinoflagellate via light microscope due to small size and morphological similarity with Pfiesteria-like dinoflagellate (PLD) species. Alternatively, we developed quantitative real-time PCR assay based on EvaGreen and determined field accessibility throughout the investigation of distribution in the entire Korean coastal waters and population dynamics in Shihwa Lake. The P. piscicida-specific primers based on internal transcribed spacer 1 (ITS 1) were designed and the specificity of primers was confirmed by PCR with other genomic DNAs which have genetic similarity with target species. Through real-time PCR assay, a standard curve which had a significant linear correlation between log cell number and
Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.
Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.
Validamycin A is an aminoglycoside fungicide produced by Streptomyces hygroscopicus that inhibits trehalase. The purpose of this study was to develop a method for detecting validamycin A in agricultural samples to establish MRL values for use in Korea. The validamycin A residues in samples were extracted using methanol/water (50/50, v/v) and purified with a hydrophilic-lipophilic balance (HLB) cartridges. The analyte was quantified and confirmed by liquid chromatograph-tandem mass spectrometer (LC-MS/MS) in positive ion mode using multiple reaction monitoring (MRM). Matrix-matched calibration curves were linear over the calibration ranges (0.005~0.5 ng) into a blank extract with
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70